Applications such as simulating complicated quantum systems or solving large-scale linear
algebra problems are very challenging for classical computers, owing to the extremely high …

Quantitative structure–activity relationship (QSAR) modelling, an approach that was
introduced 60 years ago, is widely used in computer-aided drug design. In recent years …

This chapter comprehensively explores the pivotal role of artificial intelligence (AI) in drug
discovery and development, encapsulating its potentials, methodologies, real-world …

In recent years, the interdisciplinary field of quantum computing has rapidly developed and
garnered substantial interest from both academia and industry due to its ability to process …

Context The current technology revolution has posed unexpected challenges for the
software industry. In recent years, the field of quantum computing (QC) technologies has …

When discussing research in physics and in science more generally, it is common to ascribe
equal importance to the three components of the scientific trinity: theoretical, experimental …

Highlights•Drug discovery is time consuming, expensive and experiences increasing
challenges.•Generation of new drug candidates is one of the major challenges.•Quantum …

Quantum computing and simulations are creating transformative opportunities by exploiting
the principles of quantum mechanics in new ways to generate and process information. It is …

Quantum computing holds substantial potential for applications in biology and medicine,
spanning from the simulation of biomolecules to machine learning methods for subtyping …

Numerous reports claim that quantum advantage, which should emerge as a direct
consequence of the advent of quantum computers, will herald a new era of chemical …